Statistical Properties of Convex Clustering

• Activity Number: 190
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistical Learning and Data Mining
• Author(s): Kean Ming Tan* and Daniela Witten
• Companies: University of Washington and University of Washington
• Keywords: single linkage clustering ; convex clustering ; degrees of freedom ; fusion penalty ; hierarchical clustering ; prediction error

Abstract

In this paper, we study the statistical properties of convex clustering. Through its dual problem, we establish that convex clustering is closely related to single linkage clustering. In addition, we derive the range of the tuning parameter for convex clustering that yields a non-trivial solution. We also provide an unbiased estimate of the degrees of freedom, and provide a finite sample bound for the prediction error for convex clustering. We compare convex clustering to some traditional clustering methods in a simulation study.